Generation of enzyme‐converted type O whole blood from type A whole blood: A translational study using swine whole blood
Bibliographic record
Abstract
BACKGROUND: Low-titer O whole blood (LTOWB) is increasingly used to improve trauma outcomes, but maintaining supplies remains challenging, particularly in austere environments. This study evaluated EnzAO1 (FpGalNAcDeAc) and EnzAO2 (FpGalNase) to generate enzyme-converted O type whole blood (ECO-WB) from A type swine whole blood (WB). STUDY DESIGN AND METHODS: WB from 16 A type and 4 O type swine were collected in Citrate Phosphate Dextrose Adenine-1 (CPDA-1). Type A WB was randomized to enzymatic conversion at either room temperature or 4°C. Each unit was divided into 45 mL aliquots and treated with no enzyme or one of four enzyme concentrations (1.75-17.5 μg/mL). Samples were analyzed at 15, 30, 60, and 120 min. A-antigen reduction was measured by flow cytometry. Blood counts, blood gases, rotational thromboelastometry, osmotic fragility, and free hemoglobin were used to assess blood post-conversion. RESULTS: Enzymatic treatment converted A type swine WB to ECO-WB in a concentration- and time-dependent manner. At the highest enzyme concentration (17.5 μg/mL), A antigen expression was reduced to 0.6% ± 0.2% by 15 min, comparable to the signal observed in type O controls (0.45% ± 0.45%). No significant differences in antigen conversion were observed between temperature conditions. ECO-WB demonstrated stable hematologic profiles compared to controls. DISCUSSION: This study demonstrates enzymatic conversion of type A swine WB into ECO-WB, reducing A antigen expression comparable to type O WB without compromising blood quality. The process is compatible with refrigerated and room temperature storage, supporting its application in diverse clinical and operational settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".